Increasingly retailers are looking at ways to deliver hyper-localization of assortment for their customers. We teamed up to provide an in-depth look at hyper-localization and how companies are leveraging it to drive value in their organizations.

In-store personalization today means offering the products that are most relevant for the customers of that store. That doesn’t have to mean a unique set of products at every store; a large section of what’s offered can be standard across all stores and is often referred to as a core minimum assortment (CMA). Over and above the CMA, products can be selected for an assortment because of local relevance or an established customer preference. We call this hyper-localization.

Personalizing the customer experience via hyper-localization is increasingly important. Digital commerce has transformed the retail environment, adding a new layer of complexity to the path to purchase. With customer behavior changing more frequently, many retailers are adapting their merchandising strategies and processes to increase engagement with these always-on customers.

When evaluating whether your organization is ready to embrace hyper-localization, it’s important to understand the benefits to this approach, as well as the resources and process change required.

What are you trying to achieve?

Retailers that want to win in today’s hyper-competitive environment need to focus on personalizing the customer experience. Many retailers now have access to data about their core customer base – such as whether their customers are highly affluent or price sensitive, whether they have specific ethnic needs to be filled, etc. – that influence their shopping decisions across various store locations.

Using this data to establish exactly who your customers are will help you identify the types of product you should be selling. These valuable insights can then be used to inform your hyper-localization strategy, so you can deliver a better customer experience. Not only will this increase customer loyalty but will lead to more successful category plans that drive profitable sales growth.

Understand the barriers and enablers

Your hyper-localization approach needs to align with your overarching corporate strategy, so you can ensure that your head office, store operations and supply chain systems are in sync.

With hyper-localization, planners will need to switch out assortments more regularly to address customers’ changing needs. This is not something that can be handled manually; it would require retailers to substantially expand the size of their planning staff, a prospect that is often too expensive.

Instead, many retailers are using advanced assortment optimization technology, infused with customer data science, to automate their assortment planning processes. Not only are they able to deliver a more personalized experience but with a level of efficiency that’s not possible otherwise. Depending on the commitment to hyper-localization, retailers may also want to invest additional technology to automate the localization of their space and floor plans. Without the right systems, the whole process becomes even more complex, and quite possibly unworkable.

Because hyper-localization changes how planners work, change management is a key factor to success. Changing assortments will no longer be an annual process; instead, planners will need to check their planograms frequently to determine whether a new assortment plan is needed. In this case, commitment by senior executives to support new processes and develop a culture of planogram compliance will be essential.

Also, your supply chain logistics will need to be evaluated and possibly adjusted to better support localized assortments. It’s important to consider how your warehousing assets and current supply chain partners can be used to best optimize your efficiency.

Hyper-localization at work

But to truly understand the value of hyper-localization, let’s look at how a leading grocery retailer is putting the strategy to work. The retailer recognized that its customers’ approach to shopping had started to change; they were increasingly connected via digital devices, had less time to shop and expected a personalized experience with an unprecedented amount of choice.

Meeting these changing needs with its current processes was a challenge. The retailer found that its periodic planogram reviews were not frequent enough to keep up with the rapid pace of new product introductions and discontinued items. In fact, its inability to adapt quickly enough was impacting its bottom line. In just the previous year, 3.2 million households – each averaging a 6.58 shopper visits per year – started shopping elsewhere, resulting in $1.2 billion in lost revenue for the company.

To combat this, the retailer started leveraging customer data science to personalize its store and digital experiences and drive a more local, personal and deeper relationship with its customers. As part of this process, the personalization science technology analyzed 200 million lines of customer data in each category to drive better customer insights, which were then fed into its assortment optimization technology, drastically improving the retailer’s assortments at the shelf.

By having its merchandising analytics integrated with its automated assortment planning technology, the time spent editing and revising planograms has been reduced from 6 weeks to just 60 minutes. This has made it possible for the retailer to drive deeper connections with its customers by delivering a more personalized and relevant shopping experience, both in store and online.

Don’t forget, it’s all about the customer

There are several of the benefits of adopting a hyper-localization program – the most important of which is to improve your customers’ shopping experience. Many of the retailers we know are at some stage of this journey. For retailers looking for a competitive edge, being able to efficiently meet local market needs will become an increasingly important strategy.

Watch this video to learn more about how JDA and dunnhumby are working together.

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